ArticleBiometrical journal. Biometrische Zeitschrift2016
Causal mediation analysis with a latent mediator.
Article in Biometrical journal. Biometrische Zeitschrift, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
11 citing papers in PubMed, 25 citations in OpenAlex.
- Integrating Multi-Omics with environmental data for precision health: A novel analytic framework and case study on prenatal mercury induced childhood fatty liver disease.Environment international · 2024Article
- An extension of latent unknown clustering integrating multi-omics data (LUCID) incorporating incomplete omics data.Bioinformatics advances · 2024Article
- Bayesian network mediation analysis with application to the brain functional connectome.Statistics in medicine · 2022Article
- Normalized Creatinine-to-Cystatin C Ratio and Risk of Diabetes in Middle-Aged and Older Adults: The China Health and Retirement Longitudinal Study.Diabetes & metabolism journal · 2022Article
- Penalized mediation models for multivariate data.Genetic epidemiology · 2022Article
- Associations Between Patterns of Alcohol Use and Viral Load Suppression Amongst Women Living with HIV in South Africa.AIDS and behavior · 2021Article
- Latent class mediator for multiple indicators of mediation.Statistics in medicine · 2021Article
- Penalized models for analysis of multiple mediators.Genetic epidemiology · 2020Article
- High dimensional mediation analysis with latent variables.Biometrics · 2019Article
- Generalized causal mediation and path analysis: Extensions and practical considerations.Statistical methods in medical research · 2019Article
- Accommodating a Latent XM Interaction in Statistical Mediation Analysis.Multivariate behavioral researchArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Health researchers are often interested in assessing the direct effect of a treatment or exposure on an outcome variable, as well as its indirect (or mediation) effect through an intermediate variable (or mediator). For an outcome following a nonlinear model, the mediation formula may be used to estimate causally interpretable mediation effects. This method, like others, assumes that the mediator is observed. However, as is common in structural equations modeling, we may wish to consider a latent (unobserved) mediator. We follow a potential outcomes framework and assume a generalized structural equations model (GSEM). We provide maximum-likelihood estimation of GSEM parameters using an approximate Monte Carlo EM algorithm, coupled with a mediation formula approach to estimate natural direct and indirect effects. The method relies on an untestable sequential ignorability assumption; we assess robustness to this assumption by adapting a recently proposed method for sensitivity analysis. Simulation studies show good properties of the proposed estimators in plausible scenarios. Our method is applied to a study of the effect of mother education on occurrence of adolescent dental caries, in which we examine possible mediation through latent oral health behavior.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.